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Hello everyone, I'm currently in my 4th year of a PhD in CSE(AI/ML). I'm very much interested in the position of a research scientist. Since I have hardly one year for graduation, I would like know the roadmap to achieve a good role after graduation. I would like to ask suggestions, advices and recommendations from the experts. submitted by /u/bewilderedatom...
So I am creating an app in which I intend to rank a user-inputed song according to its similarity to Jimi Hendrix songs. Similar projects have been done before and, from what I've seen, the go-to approach is to train a CNN on mel spectrograms. This is also what was suggested to me. Well, today I was talking about this in an AI discord and someone told...
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submitted by /u/Illustrious_Row_9971 [link] [comments]
Is it fair to assume that standard time series models like the ARMA and the ARIMA model are not well designed to handle "sporadic and irregular" memory patterns? As I understand, these models are usually used to handle data with well-behaved notions of "trends" and "seasonality" (e.g. you specify these in a given ARIMA model) . When you start to deal...
Hi Team, I have posted this question on one forums and would appreciate if someone can help in answering it. https://datascience.stackexchange.com/questions/96827/creating-neural-network-to-solve-for-equations The v1 variable is a mathematical expression. Currently, I am using hyperopt to solve for these parameters and am using v1,v2,v3 in regression...
Megatron-LM provides a simple yet innovative approach on how to parallelize models to train large (multi-billion parameters) language models and efficiently use GPU memory during scaling. The key point is that it does not require any major modifications (like compilation or an entirely new framework) to implement this in the existing code. It also suggested...
I'm working on data with severe class imbalance (1% is minority class) I've tried re-sampling with ratios like 1:1, 2:3..Tried over/under sampling. Getting f1 score of max 15% (Both precision and recall are poor). I've tried different algorithms, started from ridge regression, tried random forest, boosting methods. I have 25k data points to work on....
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